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  • 1.
    Arkad, Kristina
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ludwigs, Ulf
    Södersjukhuset Stockholm.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Xiao-Ming, Gao
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Medical Logic Module (MLM) representation of knowledge in a ventilator treatment advisory system1991In: International Journal of Clinical Monitoring and Computing, ISSN 0167-9945, E-ISSN 2214-7314, Vol. 8, p. 43-48Article in journal (Refereed)
  • 2.
    Bågenholm, Per
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Anderskär, Kristina
    IMT .
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Jönsson, K Å
    Dept Medicine University Hospital, Linköping.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Adding decision support to a clinical information system1994In: Technology and Health Care, ISSN 0928-7329, Vol. 1, p. 245-251Article in journal (Refereed)
  • 3.
    Collste, Göran
    et al.
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Religion and Culture, Center for Applied Ethics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    A decision support system for diabetes care: Ethical aspects1999In: Methods of Information in Medicine, ISSN 0026-1270, Vol. 38, p. 313-316Article in journal (Refereed)
  • 4.
    Erlandsson, Marcus
    et al.
    Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Health Sciences.
    Burman, Lars G.
    Swedish Institute for Infectious Disease Control, Stockholm, Sweden.
    Cars, Otto
    Swedish Institute for Infectious Disease Control, Stockholm, Sweden.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nilsson, Lennart E.
    Walther, Sten
    Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Hanberger, Håkan
    Linköping University, Department of Clinical and Experimental Medicine, Infectious Diseases . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Infectious Diseases in Östergötland.
    ICU-STRAMA Study Group,
    Prescription of antibiotic agents in Swedish intensive care units is empiric and adequate2007In: Scandinavian Journal of Infectious Diseases, ISSN 0036-5548, E-ISSN 1651-1980, Vol. 39, no 1, p. 63-69Article in journal (Refereed)
    Abstract [en]

    Since the prescription of antibiotics in the hospital setting is often empiric, particularly in the critically ill, and therefore fraught with potential error, we analysed the use of antibiotic agents in Swedish intensive care units (ICUs). We examined indications for antibiotic treatment, agents and dosage prescribed among 393 patients admitted to 23 ICUs at 7 tertiary care centres, 11 secondary hospitals and 5 primary hospitals over a 2-week period in November 2000. Antibiotic consumption was higher among ICU patients in tertiary care centres with a median of 84% (range 58-87%) of patients on antibiotics compared to patients in secondary hospitals (67%, range 35-93%) and in primary hospitals (38%, range 24-80%). Altogether 68% of the patients received antibiotics during the ICU stay compared to 65% on admission. Cefuroxime was the most commonly prescribed antibiotic before and during admission (28% and 24% of prescriptions, respectively). A date for decision to continue or discontinue antibiotic therapy was set in 21% (6/29) of patients receiving prophylaxis, in 8% (16/205) receiving empirical treatment and in 3% (3/88) when culture-based therapy was given. No correlation between antibiotic prescription and laboratory parameters such as CRP levels, leukocyte and thrombocyte counts, was found. The treatment was empirical in 64% and prophylactic in 9% of cases. Microbiological data guided prescription more often in severe sepsis (median 50%, range 40-60% of prescriptions) than in other specified forms of infection (median 32%, range 21-50%). The empirically chosen antibiotic was found to be active in vitro against the pathogens found in 55 of 58 patients (95%) with a positive blood culture. This study showed that a high proportion of ICU patients receive antimicrobial agents and, as expected, empirical-based therapy is more common than culture-based therapy. Antibiotics given were usually active in vitro against the pathogen found in blood cultures. We ascribe this to a relatively modest antibiotic resistance problem in Swedish hospitals.

  • 5.
    Erlandsson, Marcus
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Infectious Diseases . Linköping University, Faculty of Health Sciences.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nilsson, Lennart E.
    Linköping University, Department of Clinical and Experimental Medicine, Clinical Microbiology . Linköping University, Faculty of Health Sciences.
    Walther, Sten
    Department of Anaesthesiology, Ullevål University Hospital, University of Oslo, Oslo, Norway.
    Giske, Christian G.
    Division of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden.
    Jonas, Daniel
    Institute of Environmental Medicine and Hospital Epidemiology, University Medical Centre, Freiburg, Germany.
    Hanberger, Håkan
    Linköping University, Department of Clinical and Experimental Medicine, Infectious Diseases . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Infectious Diseases in Östergötland.
    Nordlinder, David
    Linköping University, Department of Clinical and Experimental Medicine, Infectious Diseases . Linköping University, Faculty of Health Sciences.
    Antibiotic susceptibility patterns and clones of Pseudomonas aeruginosa in Swedish ICUs2008In: Scandinavian Journal of Infectious Diseases, ISSN 0036-5548, E-ISSN 1651-1980, Vol. 40, no 6-7, p. 487-494Article in journal (Refereed)
    Abstract [en]

    Pseudomonas aeruginosa is 1 of the bacteria most adaptive to anti-bacterial treatment. Previous studies have shown nosocomial spread and transmission of clonal strains of P. aeruginosa in European hospitals. In this study we investigated antibiotic susceptibility and clonality in 101 P. aeruginosa isolates from 88 patients admitted to 8 Swedish ICUs during 2002. We also compared phenotypes and genotypes of P. aeruginosa and carried out cluster analysis to determine if phenotypic data can be used for surveillance of clonal spread. All isolates were collected on clinical indication as part of the NPRS II study in Sweden and were subjected to AFLP analysis for genotyping. 68 isolates with unique genotypes were found. Phenotyping was performed using MIC values for 5 anti-pseudomonal agents. Almost 6% of the isolates were multi-drug resistant (MDR), and this figure rose to almost 8% when intermediate isolates were also included. We found probable clonal spread in 9 cases, but none of them was found to be an MDR strain. Phenotypical cluster analysis produced 40 clusters. Comparing partitions did not demonstrate any significant concordance between the typing methods. The conclusion of our study is that cross-transmission and clonal spread of MDR P. aeruginosa does not present a clinical problem in Swedish ICUs, but probable cross-transmission of non-MDR clones indicate a need for improved hygiene routines bedside. The phenotype clusters were not concordant with genotype clusters, and genotyping is still recommended for epidemiological tracking.

  • 6.
    Fransson, G
    et al.
    Department of Geriatrics and Rehab, County Hospital, Kalmar, Sweden.
    Berkius, J
    Department of Anaesthesia and Intensive Care, Västervik Hospital, Sweden.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Kahlmeter, G
    Department of Clinical Microbiology, Central Hospital, Växjö, Sweden.
    Hanberger, Håkan
    Linköping University, Department of Molecular and Clinical Medicine, Infectious Diseases. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Infectious Diseases in Östergötland.
    Walther, Sten
    Surgical ICU, Ullevål University Hospital, Oslo, Norway.
    Linking local microbiology databases with the Swedish Intensive Care Registry to examine impact of bacterial resistance on the critically ill.2007In: Acta anaesthesiologica Scandinavica. Volume 51, Issue Supplement s118, Malden, MA, United States: Wiley-Blackwell, 2007, Vol. 51, p. 33-33 (Poster 25)Conference paper (Other academic)
    Abstract [en]

    Background and aims: Bacterial resistance to antibiotics hasemerged as an important factor influencing patient mortalityand morbidity. The overall purpose of this project is to exam-ine the impact of bacterial resistance on resource use andoutcome in the critically ill. The aims of the current report isto demonstrate that linkage of local microbiology databasesand the Swedish Intensive Care Registry (SIR) was possibleand to provide a preliminary analysis of data from a sub-group of ICU patients (chronic obstructive pulmonary dis-ease, COPD).

    Methods: Admissions due to an acute exacerbation of COPDwere matched with bacteriology samples obtained 14 daysbefore ICU admission, during ICU stay and 14 days after dis-charge from ICU by linking six local microbiology databaseswith patient data in SIR. Linkage was by the patient’s uniquepersonal number and ICU admission and discharge days.

    Results: We found 195 patients with median APACHE II prob-ability 0.22 (iqr 0.12–0.37), median length of stay (LOS) 46 (iqr 21–125) hours and 79% 30 day survival. Cultures from 2 weeks before (n=128), during ICU-stay (n=750) and from14 days after ICU discharge (n=228) were identified. During ICU stay airways (n=261), blood or intravascular devices (n=246) and other sites (n=243) were cultured. The totalnumber of airway cultures per patient increased linearly withlength of stay (P<0.01,r2= 0.61). Gram-negative bacteria were most common in positive airway cultures (41%) followedby Candida spp (22%), while positive blood cultures were pre-dominantly Gram-positive (71%). 30-day-mortality was 10/53 with positive and 10/29 with negative airway cultures(P=0.23).

    Conclusion: Linkage of local microbiology databases and theSwedish Intensive Care Registry is possible and can generate information that may be used to examine relationships between bacterial resistance and outcomes in the critically illpatient.

  • 7.
    Gill, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ludwigs, Ulf
    Södersjukhuset Stockholm.
    Matell, George
    Södersjukhuset Stockholm.
    Rudowski, Robert
    Polish Academy of Sciences Warszawa.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    ström, Christer
    Siemens Elema Solna.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Integrating knowledge-based technology into computer aided ventilation systems1990In: International Journal of Clinical Monitoring and Computing, ISSN 0167-9945, E-ISSN 2214-7314, Vol. 7Article in journal (Refereed)
  • 8.
    Gill, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Computer communication based on PABX-technique1990In: IMIA Conference on Telematics in Medicine 1990,1990, Elsevier Science Publ , 1990Conference paper (Refereed)
  • 9.
    Hanberger, Håkan
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Infectious Diseases . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Infectious Diseases in Östergötland.
    Arman, Dilek
    Gazi University School of Medicine.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Jindrák, Vlastimil
    Na Homolce Hospital, Praha, Czech Republic.
    Kalenic, Smilja
    Clinical Hospital Centre, Zagreb, Croatia.
    Kurcz, Andrea
    National Centre for Epidemiologia, Budapest, Hungary.
    Licker, Monica
    “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania.
    Naaber, Paul
    United Laboratories, Tartu University Clinics.
    Scicluna, Elizabeth A.
    Mater Dei Hospital, Malta .
    Vanis, Václav
    Na Homolce Hospital, Praha, Czech Republic.
    Walther, Sten M.
    Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Surveillance of microbial resistance in European Intensive Care Units: a first report from the Care-ICU programme for improved infection control2009In: Intensive Care Medicine, ISSN 0342-4642, E-ISSN 1432-1238, Vol. 35, no 1, p. 91-100Article in journal (Refereed)
    Abstract [en]

    Purpose: To report initial results from a European ICU surveillance programme focussing on antibiotic consumption, microbial resistance and infection control.

    Methods: Thirty-five ICUs participated during 2005. Microbial resistance, antibiotic consumption and infection control stewardship measures were entered locally into a web-application. Results were validated locally, aggregated by project leaders and fed back to support local audit and benchmarking.

    Results: Median (range) antibiotic consumption was 1,254 (range 348–4,992) DDD per 1,000 occupied bed days. The proportion of MRSA was median 11.6% (range 0–100), for ESBL phenotype of E. coli and K. pneumoniae 3.9% (0–80) and 14.3% (0–77.8) respectively, and for carbapenem-resistant P. aeruginosa 22.5% (0–100). Screening on admission for alert pathogens was commonly omitted, and there was a lack of single rooms for isolation.

    Conclusions: The surveillance programme demonstrated wide variation in antibiotic consumption, microbial resistance and infection control measures. The programme may, by providing rapid access to aggregated results, promote local and regional audit and benchmarking of antibiotic use and infection control practices.

  • 10.
    Hanberger, Håkan
    et al.
    Linköping University, Department of Molecular and Clinical Medicine, Infectious Diseases. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Infectious Diseases in Östergötland.
    Burman, LG
    Cars, O
    Erlandsson, Marcus
    Linköping University, Department of Molecular and Clinical Medicine, Infectious Diseases. Linköping University, Faculty of Health Sciences.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nilsson, Lennart
    Linköping University, Department of Molecular and Clinical Medicine, Clinical Microbiology. Linköping University, Faculty of Health Sciences.
    Nordlinder, D
    Walther, Sten
    Linköping University, Department of Medicine and Care, Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Low antibiotic resistance rates in Staphylococcus aureus, Escherichia coli and Klebsiella spp but not in Enterobacter spp and Pseudomonas aeruginosa: A prospective observational study in 14 Swedish ICUs over a 5-year period2007In: Acta Anaesthesiologica Scandinavica, ISSN 0001-5172, E-ISSN 1399-6576, Vol. 51, no 7, p. 937-941Article in journal (Refereed)
    Abstract [en]

    Background: Intensive care units (ICUs) are hot zones for emergence and spread of antibiotic resistance because of frequent invasive procedures, antibiotic usage and transmission of bacteria. We report prospective data on antibiotic use and bacterial resistance from 14 academic and non-academic ICUs, participating in the ICU-STRAMA programme 1999-2003. Methods: The quantity of antibiotics delivered to each ICU was calculated as defined daily doses per 1000 occupied bed days (DDD1000). Specimens for culture were taken on clinical indications and only initial isolates were considered. Species-related breakpoints according to the Swedish Reference Group for Antibiotics were used. Antibiotic resistance was defined as the sum of intermediate and resistant strains. Results: Mean antibiotic use increased from 1245 DDD1000 in 1999 to 1510 DDD1000 in 2003 (P = 0.11 for trend). Of Staphylococcus aureus, 0-1.8% were methicillin resistant (MRSA). A presumptive extended spectrum beta-lactamase (ESBL) phenotype was found in <2.4% of Escherichia coli, based on cefotaxime susceptibility, except a peak in 2002 (4.6%). Cefotaxime resistance was found in 2.6-4.9% of Klebsiella spp. Rates of resistance among Enterobacter spp. to cefotaxime (20-33%) and among Pseudomonas aeruginosa to imipenem (22-33%) and ciprofloxacin (5-21%) showed no time trend. Conclusion: MRSA and cefotaxime-resistant E. coli and Klebsiella spp strains were few despite high total antibiotic consumption. This may be the result of a slow introduction of resistant strains into the ICUs, and good infection control. The cause of imipenem and ciprofloxacin resistance in P. aeruginosa could reflect the increased consumption of these agents plus spread of resistant clones. © 2007 The Authors.

  • 11.
    Hanberger, Håkan
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Infectious Diseases . Linköping University, Faculty of Health Sciences.
    Erlandsson, Marcus
    Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Health Sciences.
    Burman, Lars G.
    Swedish Institute for Infectious Diseases Control, Solna, Sweden.
    Cars, Otto
    Swedish Institute for Infectious Diseases Control, Solna, Sweden.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Lindgren, Sune
    Nilsson, Lennart E.
    Linköping University, Department of Clinical and Experimental Medicine, Clinical Microbiology . Linköping University, Faculty of Health Sciences.
    Olsson-Liljequist, Barbro
    Swedish Institute for Infectious Diseases Control, Solna, Sweden.
    Walther, Sten
    Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    High Antibiotic Susceptibility Among Bacterial Pathogens In Swedish ICUs2004In: Scandinavian Journal of Infectious Diseases, ISSN 0036-5548, Vol. 36, no 1, p. 24-30Article in journal (Refereed)
    Abstract [en]

    Local infection control measures, antibiotic consumption and patient demographics from 1999-2000 together with bacteriological analyses were investigated in 29 ICUs participating in the ICU-STRAMA programme. The median antibiotic consumption per ICU was 1147 (range 605-2143) daily doses per 1000 occupied bed d (DDD1000). Antibiotics to which >90% of isolates of an organism were susceptible were defined as treatment alternatives (TA90). The mean number of TA90 was low (1-2 per organism) for Enterococcus faecium (vancomycin:VAN), coagulase negative staphylococci (VAN), Pseudomonas aeruginosa (ceftazidime:CTZ, netilmicin: NET) and Stenotrophomonas maltophilia (CTZ, trimethoprim-sulfamethoxazole: TSU), but higher (3-7) for Acinetobacter spp. (imipenem:IMI, NET, TSU), Enterococcus faecalis (ampicillin:AMP, IMI, VAN), Serratia spp. (ciprofloxacin:CIP, IMI, NET), Enterobacter spp. (CIP, IMI, NET, TSU), E. coli (cefuroxime:CXM, cefotaxime/ceftazidime:CTX/CTZ, CIP, IMI, NET, piperacillin-tazobactam:PTZ, TSU), Klebsiella spp. (CTX/CTZ CIP, IMI, NET, PTZ, TSU) and Staphylococcus aureus (clindamycin, fusidic acid, NET, oxacillin, rifampicin, VAN). Of S. aureus isolates 2% were MRSA. Facilities for alcohol hand disinfection at each bed were available in 96% of the ICUs. The numbers of TA90 available were apparently higher than in ICUs in southern Europe and the US, despite a relatively high antibiotic consumption. This may be due to a moderate ecological impact of the used agents and the infection control routines in Swedish ICUs.

  • 12.
    Karlsson, Daniel
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ekdahl, Christer
    Linköping University, Department of Molecular and Clinical Medicine.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Forsum, Urban
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Molecular and Clinical Medicine, Clinical Microbiology. Östergötlands Läns Landsting, Centre for Laboratory Medicine, Department of Clinical Microbiology.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    A WWW-based decision-support system using medical logic modules and hypertext1996In: Medical Informatics Europe 96,1996, Amsterdam: IOS Press , 1996, p. 93-Conference paper (Refereed)
  • 13.
    Karlsson, Daniel
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Ekdahl, Christer
    Linköping University, Department of Clinical and Experimental Medicine, Infectious Diseases. Linköping University, Faculty of Health Sciences.
    Wigertz, Ove
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Forsum, Urban
    Linköping University, Department of Clinical and Experimental Medicine, Clinical Microbiology. Linköping University, Faculty of Health Sciences.
    Extended telemedical consultation using Arden Syntax based decision support, hypertext and WWW technique1997In: Methods of Information in Medicine, ISSN 0026-1270, Vol. 36, no 2, p. 108-114Article in journal (Refereed)
    Abstract [en]

    There is an obvious need for geographic distribution of expert knowledge among several health care units without increasing the cost of on-site expertise in locations where health care is provided. This paper describes the design of a knowledge-based decision-support system for extended consultation in clinical medicine. The system is based on Arden Syntax for Medical Logic Modules and hypertext using World Wide Web technology. It provides advice and explanations regarding the given advice. The explanations are presented in a hypertext format allowing the user to browse related information and to verify the relevance of the given advice. The system is intended to be used in a closed local network. With special precautions regarding issues of safety and patient security, the system can be used over wider areas such as in rural medicine. A prototype has been developed in the field of clinical microbiology and infectious diseases regarding infective endocarditis.

  • 14.
    Kjellgren, Karin
    et al.
    Hälsouniversitet Linköping.
    Ahlner, Johan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Pharmacology.
    Dahlöf, Björn
    Sahlgrenska sjukhuset Göteborg.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Patients' and physicians' assessment of risks associated with hypertension and benefits from treatment1998In: Journal of Cardiovascular Risk, ISSN 1350-6277, E-ISSN 1473-5652, Vol. 5, p. 161-166Article in journal (Refereed)
  • 15.
    Kjellgren, Karin
    et al.
    Hälsouniveristetet LInköping.
    Ahlner, Johan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Pharmacology.
    Dahlöf, Björn
    Sahlgrenska sjukhuset Göteborg.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Perceived symptoms amongst hypertensive patients in routine clinical practice - a population-based study1998In: Journal of Internal Medicine, ISSN 0954-6820, E-ISSN 1365-2796, Vol. 244, p. 325-332Article in journal (Refereed)
  • 16.
    Lindholm, P
    et al.
    Karolinska Institutet .
    Karlsson, L
    Karolinska Institutet .
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Linnarsson, Dag
    Dept of Physiology and Pharmacology Karolinska Institutet.
    Time components of circulatory transport from the lungs to a peripheral artery in humans2006In: European Journal of Applied Physiology, ISSN 1439-6319, E-ISSN 1439-6327, Vol. 97, no 1, p. 96-102Article in journal (Refereed)
    Abstract [en]

    Blood gas changes occurring in the lung undergo delay and damping on their way to a peripheral artery sampling site. Knowledge of the time components of circulatory transfer is important for the understanding of respiratory control and cardiovascular reflexes in response to blood gas transients. Providing steady state with regard to V̇A/ Q̇ distribution, cardiac output and peripheral blood flow, the relationship between the time courses of small end-tidal and peripheral PO2 changes is determined by the transfer function of the interposed vascular segment. This transfer function, expressed as delay time TD and mean transit time (MTT), was measured in six well-trained subjects, allowing the calculation of arterial time-courses from end-tidal to the reverse. They were studied at rest and during four different dynamic leg exercise intensities in the supine posture. TD and MTT amounted to 15.8 ± 1.7 (mean ± SEM) and 18.3 ± 2.1 s at rest and were shortened to 7.7 ± 0.6 and 11.5 ± 1.8 s during exercise at 170 W. The shortening of TD and MTT did not appear to be simply an inverse function of cardiac output, suggesting that the shortening occurs in the central circulatory segment but not in the arm segment. © Springer-Verlag 2006.

  • 17.
    Magyar, Gabor
    et al.
    IMT LiU .
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ericsson, K-E
    Östgötadata Linköping.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Xiao-Ming, Gao
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Linnarsson, Rolf
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Realizing medical knowledge in MLM form as working modules in a patient information system1991In: IMIA Software Engineering in Medical Informatics,1991, Elsevier Science Publ , 1991, p. 481-Conference paper (Refereed)
  • 18.
    Magyar, Gabor
    et al.
    IMT LiU.
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Xiao-Ming, Gao
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Strategies for efficient implementation of the Arden Syntax for medical decision support1991In: MIE91,1991, Berlin: Springer Verlag , 1991, p. 222-Conference paper (Refereed)
  • 19.
    Petersson, Håkan
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    A variance-based measure of inter-rater agreement in medical databases2002In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 35, no 5-6, p. 331-342Article in journal (Refereed)
    Abstract [en]

    The increasing use of encoded medical data requires flexible tools for data quality assessment. Existing methods are not always adequate, and this paper proposes a new metric for inter-rater agreement of aggregated diagnostic data. The metric, which is applicable in prospective as well as retrospective coding studies, quantifies the variability in the coding scheme, and the variation can be differentiated in categories and in coders. Five alternative definitions were compared in a set of simulated coding situations and in the context of mortality statistics. Two of them were more effective, and the choice between them must be made according to the situation. The metric is more powerful for larger numbers of coded cases, and Type I errors are frequent when coding situations include different numbers of cases. We also show that it is difficult to interpret the meaning of variation when the structures of the compared coding schemes differ.

  • 20.
    Petersson, Håkan
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Improving inter-rater reliability by coding scheme reorganization: managing signs and symptomsManuscript (preprint) (Other academic)
    Abstract [en]

    The aim of this paper is to study the potential for improving inter-rater reliability in general practice registries through the use of a semantic terminology model that enables diagnostic labels to be separated into symptoms and diseases, i.e. into different levels of diagnostic precision. Cases coded as symptoms according to the ICD-based coding system currently in use in Swedish general practice were reclassified with the help of the model, and inter-rater variability was measured through divergences of observed coding distributions from expected distributions. 40 percent of the symptom cases were candidates for reclassification; half of these could actually be reclassified. This decreased inter-rater variability, but the difference was not statistically significant. Diagnostic categories with large variation in utilization rates were foWld, which calls for careful selection of topics for medical audit. Although reclassification of symptoms may improve reliability, no straightforward association was found between a chapter's diagnostic precision and its contribution to overall variability. Nor could differences in diagnostic precision explain all variation within a chapter. Further research on other dimensions of the coding system is needed before symptom reclassification can be recommended as a general reliability-improving tool.

  • 21.
    Petersson, Håkan
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Improving Inter-Rater Reliability through Coding Scheme Reorganization: Managing Signs and Symptoms2008In: The First Conference on Text and Data Mining of Clinical Documents Louhi08,2008, Turku: TUCS General Publications , 2008, p. 54-Conference paper (Refereed)
  • 22.
    Razavi, Amir R
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Non-compliance with a postmastectomy radiotherapy guideline: Decision tree and cause analysis2008In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 8, no 41Article in journal (Refereed)
    Abstract [en]

    Background: The guideline for postmastectomy radiotherapy (PMRT), which is prescribed to reduce recurrence of breast cancer in the chest wall and improve overall survival, is not always followed. Identifying and extracting important patterns of non-compliance are crucial in maintaining the quality of care in Oncology.

    Methods: Analysis of 759 patients with malignant breast cancer using decision tree induction (DTI) found patterns of non-compliance with the guideline. The PMRT guideline was used to separate cases according to the recommendation to receive or not receive PMRT. The two groups of patients were analyzed separately. Resulting patterns were transformed into rules that were then compared with the reasons that were extracted by manual inspection of records for the non-compliant cases.

    Results: Analyzing patients in the group who should receive PMRT according to the guideline did not result in a robust decision tree. However, classification of the other group, patients who should not receive PMRT treatment according to the guideline, resulted in a tree with nine leaves and three of them were representing non-compliance with the guideline. In a comparison between rules resulting from these three non-compliant patterns and manual inspection of patient records, the following was found:

    In the decision tree, presence of perigland growth is the most important variable followed by number of malignantly invaded lymph nodes and level of Progesterone receptor. DNA index, age, size of the tumor and level of Estrogen receptor are also involved but with less importance. From manual inspection of the cases, the most frequent pattern for non-compliance is age above the threshold followed by near cut-off values for risk factors and unknown reasons.

    Conclusion: Comparison of patterns of non-compliance acquired from data mining and manual inspection of patient records demonstrates that not all of the non-compliances are repetitive or important. There are some overlaps between important variables acquired from manual inspection of patient records and data mining but they are not identical. Data mining can highlight non-compliance patterns valuable for guideline authors and for medical audit. Improving guidelines by using feedback from data mining can improve the quality of care in oncology.

  • 23.
    Razavi, Amir Reza
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Stål, Olle
    Linköping University, Department of Clinical and Experimental Medicine, Oncology . Linköping University, Faculty of Health Sciences.
    Sundquist, Marie
    Department of Surgery, County Hospital, Kalmar, Sweden.
    Thorstenson, Sten
    Department of Pathology, County Hospital, Kalmar, Sweden.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    The South-East Swedish Breast Cancer Study Group,
    Exploring cancer register data to find risk factors for recurrence of breast cancer: Application of Canonical Correlation Analysis2005In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, Vol. 5, no 29, p. 29-35Article in journal (Refereed)
    Abstract [en]

    Background

    A common approach in exploring register data is to find relationships between outcomes and predictors by using multiple regression analysis (MRA). If there is more than one outcome variable, the analysis must then be repeated, and the results combined in some arbitrary fashion. In contrast, Canonical Correlation Analysis (CCA) has the ability to analyze multiple outcomes at the same time.

    One essential outcome after breast cancer treatment is recurrence of the disease. It is important to understand the relationship between different predictors and recurrence, including the time interval until recurrence. This study describes the application of CCA to find important predictors for two different outcomes for breast cancer patients, loco-regional recurrence and occurrence of distant metastasis and to decrease the number of variables in the sets of predictors and outcomes without decreasing the predictive strength of the model.

    Methods

    Data for 637 malignant breast cancer patients admitted in the south-east region of Sweden were analyzed. By using CCA and looking at the structure coefficients (loadings), relationships between tumor specifications and the two outcomes during different time intervals were analyzed and a correlation model was built.

    Results

    The analysis successfully detected known predictors for breast cancer recurrence during the first two years and distant metastasis 2–4 years after diagnosis. Nottingham Histologic Grading (NHG) was the most important predictor, while age of the patient at the time of diagnosis was not an important predictor.

    Conclusion

    In cancer registers with high dimensionality, CCA can be used for identifying the importance of risk factors for breast cancer recurrence. This technique can result in a model ready for further processing by data mining methods through reducing the number of variables to important ones.

  • 24.
    Razavi, Amir Reza
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    A Data Mining Approach to Analyze Non-compliance with a Guideline for the Treatment of Breast Cancer2007In: Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365, Vol. 129, p. 591-597Article in journal (Refereed)
    Abstract [en]

    Postmastectomy radiotherapy (PMRT) is prescribed in order to reduce the local recurrence of breast cancer and improve overall survival. A guideline supports the trade-off between benefits and adverse effects of PMRT. However, this guideline is not always followed in practice. This study tries to find a method for revealing patterns of non-compliance between the actual treatment and the PMRT guideline.

    Data from breast cancer patients admitted to Linköping University Hospital between 1990 and 2000 were analyzed in this study. Cases that were not treated in accordance with the guideline were selected and analyzed by decision tree induction (DTI). Thereafter, four resulting rules, as representations for groups of patients, were compared to the guideline.

    Finding patterns of non-compliance with guidelines by means of rules can be an appropriate alternative to manual methods, i.e. a case-by-case comparison when studying very large datasets. The resulting rules can be used in a knowledge base of a guideline-based decision support system to alert when inconsistencies with the guidelines may appear.

  • 25.
    Razavi, Amir Reza
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    A data mining approach to build a predictive model for breast cancer recurrence2006In: Annual Workshop of the Swedish Intelligence Society SAIS2006,2006, 2006, p. 51-55Conference paper (Other academic)
    Abstract [en]

        

  • 26.
    Razavi, Amir Reza
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    A Data Pre-processing Method to Increase Efficiency and Accuracy in Data Mining2005In: 10th Conference on Artificial Intelligence in Medicine, AIME2005 - Aberdeen, UK / [ed] Miksch, Silvia, Hunter, Jim, Keravnou, Elpida, 2005, p. 434-443Conference paper (Other academic)
    Abstract [en]

    In medicine, data mining methods such as Decision Tree Induction (DTI) can be trained for extracting rules to predict the outcomes of new patients. However, incompleteness and high dimensionality of stored data are a problem. Canonical Correlation Analysis (CCA) can be used prior to DTI as a dimension reduction technique to preserve the character of the original data by omitting non-essential data. In this study, data from 3949 breast cancer patients were analysed. Raw data were cleaned by running a set of logical rules. Missing values were replaced using the Expectation Maximization algorithm. After dimension reduction with CCA, DTI was employed to analyse the resulting dataset. The validity of the predictive model was confirmed by ten-fold cross validation and the effect of pre-processing was analysed by applying DTI to data without pre-processing. Replacing missing values and using CCA for data reduction dramatically reduced the size of the resulting tree and increased the accuracy of the prediction of breast cancer recurrence.

  • 27.
    Razavi, Amir Reza
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Canonical correlation analysis for data reduction in data mining applied to predictive models for breast cancer recurrence2005In: The XIXth International Congress of the European Federation for Medical Informatics,2005, Amsterdam: IOSPress , 2005, p. 175-180Conference paper (Refereed)
    Abstract [en]

    Data mining methods can be used for extracting specific medical knowledge such as important predictors for recurrence of breast cancer in pertinent data material. However, when there is a huge quantity of variables in the data material it is first necessary to identify and select important variables. In this study we present a preprocessing method for selecting important variables in a dataset prior to building a predictive model. In the dataset, data from 5787 female patients were, analysed. To cover more predictors and obtain a better assessment of the outcomes, data were retrieved from three different registers: the regional breast cancer, tumour markers, and cause of death registers. After retrieving information about selected predictors and outcomes from the different registers, the raw data were cleaned by running different logical rules. Thereafter, domain experts selected predictors assumed to be important regarding recurrence of breast cancer. After that, Canonical Correlation Analysis (CCA) was applied as a dimension reduction technique to preserve the character of the original data. Artificial Neural Network (ANN) was applied to the resulting dataset for two different analyses with the same settings. Performance of the predictive models was confirmed by ten-fold cross validation. The results showed an increase in the accuracy of the prediction and reduction of the mean absolute error.

  • 28.
    Razavi, Amir Reza
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Data Mining Approach to Analyze Non-compliance with a Guideline for the Treatment of Breast Cancer2007In: MEDINFO 2007: PROCEEDINGS OF THE 12TH WORLD CONGRESS ON HEALTH (MEDICAL) INFORMATICS, PTS 1 AND 2, IOS Press, 2007, p. 591-595Conference paper (Refereed)
    Abstract [en]

    Postmastectomy radiotherapy (PAMT) is prescribed in order to reduce the local recurrence of breast cancer and improve overall survival. A guideline supports the trade-off between benefits and adverse effects of PMRT However, this guideline is not always followed in practice. This study tries to find a method for revealing patterns of noncompliance between the actual treatment and the PMRT guideline.Data from breast cancer patients admitted to Linkoping University Hospital between 1990 and 2000 were analyzed in this study. Cases that were not treated in accordance with the guideline were selected and analyzed by decision tree induction (DTI). Thereafter, four resulting rules, as representations for groups of patients, were compared to the guideline.Finding patterns of non-compliance with guidelines by means of rules can be an appropriate alternative to manual methods, i.e. a case-by-case comparison when studying very large datasets. The resulting rules can be used in a knowledge base of a guideline-based decision support system to alert when inconsistencies with the guidelines may appear.

  • 29.
    Razavi, Amir Reza
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Predicting metastasis in breast cancer: comparing a decision tree with domain experts2007In: Journal of Medical Systems, ISSN 0148-5598, Vol. 31, no 4, p. 263-273Article in journal (Refereed)
    Abstract [en]

    Breast malignancy is the second most common cause of cancer death among women in Western countries. Identifying high-risk patients is vital in order to provide them with specialized treatment. In some situations, such as when access to experienced oncologists is not possible, decision support methods can be helpful in predicting the recurrence of cancer. Three thousand six hundred ninety-nine breast cancer patients admitted in south-east Sweden from 1986 to 1995 were studied. A decision tree was trained with all patients except for 100 cases and tested with those 100 cases. Two domain experts were asked for their opinions about the probability of recurrence of a certain outcome for these 100 patients. ROC curves, area under the ROC curves, and calibration for predictions were computed and compared. After comparing the predictions from a model built by data mining with predictions made by two domain experts, no significant differences were noted. In situations where experienced oncologists are not available, predictive models created with data mining techniques can be used to support physicians in decision making with acceptable accuracy.

  • 30.
    Razavi, Amir Reza
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Stachowicz, Marian S.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    An approach for generating fuzzy rules from decision trees2006In: Ubiquity: Technologies for Better Health in Aging Societies - Proceedings of MIE2006 / [ed] Arie Hasman, Reinhold Haux, Johan van der Lei, Etienne De Clercq, Francis Roger-France, IOS Press , 2006, p. 581-586Conference paper (Refereed)
    Abstract [en]

    Identifying high-risk breast cancer patients is vital both for clinicians and for patients. Some variables for identifying these patients such as tumor size are good candidates for fuzzification. In this study, Decision Tree Induction (DTI) has been applied to 3949 female breast cancer patients and crisp If-Then rules has been acquired from the resulting tree. After assigning membership functions for each variable in the crisp rules, they were converted into fuzzy rules and a mathematical model was constructed. One hundred randomly selected cases were examined by this model and compared with crisp rules predictions. The outcomes were examined by the area under the ROC curve (AUC). No significant difference was noticed between these two approaches for prediction of recurrence of breast cancer. By soft discretization of variables according to resulting rules from DTI, a predictive model, which is both more robust to noise and more comprehensible for clinicians, can be built.

  • 31.
    Ridderstolpe, Lisa
    et al.
    Linköping University, Department of Biomedical Engineering. Östergötlands Läns Landsting, Heart Centre, Department of Cardiology. Linköping University, Faculty of Health Sciences.
    Ahlgren, Ewa
    Linköping University, Department of Biomedical Engineering. Östergötlands Läns Landsting, Heart Centre, Department of Cardiology. Linköping University, Faculty of Health Sciences.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering. Östergötlands Läns Landsting, Heart Centre, Department of Cardiology. Linköping University, Faculty of Health Sciences.
    Ruthberg, Hans
    Linköping University, Department of Biomedical Engineering. Östergötlands Läns Landsting, Heart Centre, Department of Cardiology. Linköping University, Faculty of Health Sciences.
    Risk factor analysis of early and delayed cerebral complications after cardiac surgery2002In: Journal of Cardiothoracic and Vascular Anesthesia, ISSN 1053-0770, E-ISSN 1532-8422, Vol. 16, no 3, p. 278-285Article in journal (Refereed)
    Abstract [en]

    Objective: To report the incidence, severity, and possible risk factors for early and delayed cerebral complications.

    Design: Retrospective study.

    Setting: Linköping University Hospital, Sweden.

    Participants: Consecutive patients who underwent cardiac surgery in the period July 1996 through June 2000 (n = 3,282).

    Interventions: A standard cardiopulmonary bypass (CPB) technique was used for most patients. Postoperative anticoagulant treatment included heparin or anti-Xa dalteparin. Patients undergoing coronary artery bypass graft surgery received acetylsalicylic acid, and patients undergoing valve surgery received warfarin.

    Measurements and Main Results: Cerebral complications occurred in 107 patients (3.3%). Of these, 60 (1.8%) were early, and 33 (1.0%) were delayed, and in 14 (0.4%) patients the onset was unknown. There were 37 variables in univariate analysis (p < 0.15) and 14 variables in multivariate analysis (p < 0.05) associated with cerebral complications. Predictors of early cerebral complications were older age, preoperative hypertension, aortic aneurysm surgery, prolonged CPB time, hypotension at CPB completion and soon after CPB, and postoperative arrhythmia and supraventricular tachyarrhythmia. Predictors of delayed cerebral complications were female gender, diabetes, previous cerebrovascular disease, combined valve surgery and coronary artery bypass graft surgery, postoperative supraventricular tachyarrhythmia, and prolonged ventilator support. Early cerebral complications seem to be more serious, with more permanent deficits and a higher overall mortality (35.0% v 18.2%).

    Conclusion: Most cerebral complications had an early onset. The results of this study suggest that aggressive antiarrhythmic treatment and blood pressure control may imfurther prove the cerebral outcome after cardiac surgery.

  • 32.
    Ridderstolpe, Lisa
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Borga, Magnus
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Rutberg, Hans
    Östergötlands Läns Landsting, Heart Centre.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Canonical correlation analysis of risk factors and clinical outcomes in cardiac surgery2005In: Journal of medical systems, ISSN 0148-5598, E-ISSN 1573-689X, Vol. 29, no 4, p. 357-377Article in journal (Refereed)
    Abstract [en]

    Assessment of the association between risk factors and outcomes in cardiac surgery is a complex problem. The aim of this study was to explore the relationship between possible risk factors and several clinical outcomes in cardiac surgery by using canonical correlation analysis (CCA). This retrospective study of 2605 consecutive adult patients who underwent cardiac surgery, evaluated 74 potential risk factors and up to 12 outcomes by canonical correlation analysis. For three serious outcomes, sternal wound complications/mediastinitis, cerebral complications, and perioperative myocardial infarctions, CCA was preceded by univariate analyses and backward stepwise multivariate logistic regression analyses. The CCA suggests that the major risk factors for complications in these models are intraoperative and postoperative risk factors. The power of risk prediction models developed with multivariate regression analysis can be enhanced by application of canonical correlation analysis, thereby offering new ways of analyzing and interpreting sets of potential risk factors in relation to sets of clinical outcomes.

  • 33.
    Ridderstolpe, Lisa
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Granfeldt, Hans
    Linköping University, Department of Medicine and Care, Thoracic Surgery. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ruthberg, Hans
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Anaesthesiology. Östergötlands Läns Landsting, Anaesthesiology and Surgical Centre, Department of Intensive Care UHL.
    Superficial and deep sternal wound complications: Incidence, risk factors and mortality2001In: European Journal of Cardio-Thoracic Surgery, ISSN 1010-7940, E-ISSN 1873-734X, Vol. 20, no 6, p. 1168-1175Article in journal (Refereed)
    Abstract [en]

    Objectives: Sternal wound complications often have a late onset and are detected after patients are discharged from the hospital. In an effort to catch all sternal wound complications, different postdischarge surveillance methods have to be used. Together with this long-term follow-up an analysis of risk factors may help to identify patients at risk and can lead to more effective preventive and control measures.

    Methods: This retrospective study of 3008 adult patients who underwent consecutive cardiac surgery from January 1996 through September 1999 at Link÷ping University Hospital, Sweden, evaluated 42 potential risk factors by univariate analysis followed by backward stepwise multivariate logistic regression analysis.

    Results: Two-thirds of the 291 (9.7%) sternal wound complications that occurred were identified after discharge. Of the 291 patients, 47 (1.6%) had deep sternal infections, 50 (1.7%) had postoperative mediastinitis, and 194 (6.4%) had superficial sternal wound complications. Twenty-three variables were selected by univariate analysis (P<0.15) and included in a multivariate analysis where eight variables emerged as significant (P<0.05). Preoperative risk factors for deep sternal infections/mediastinitis were obesity, insulin-dependent diabetes, smoking, peripheral vascular disease, and high New York Heart Association score. An intraoperative risk factor was bilateral use of internal mammary arteries, and a postoperative risk factor was prolonged ventilator support. Risk factors for superficial sternal wound complications were obesity, and an age of

  • 34.
    Rudowski, Robert
    et al.
    Polish Academy of Science Warsaw.
    Bokliden, Annette
    Södersjukhuset Stockholm.
    Carstensen, Anders
    SÖdersjukhuset Stockholm.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ludwigs, Ulf
    Södersjukhuset Stockholm.
    Matell, George
    Södersjukhuset Stockholm.
    Multivariable optimization of mechanical ventilation. A linear programming approach1991In: International Journal of Clinical Monitoring and Computing, ISSN 0167-9945, E-ISSN 2214-7314, Vol. 8, p. 107-115Article in journal (Refereed)
  • 35.
    Rudowski, Robert
    et al.
    Inst Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Waraw.
    Frostell, Clas
    Danderyds sjukhus .
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    A knowledge-based support system for mechanical ventilation of hte lungs. The KUSIVAR concept and prototype1989In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 30, p. 59-70Article in journal (Refereed)
  • 36.
    Rudowski, Robert
    et al.
    Polish Acadmy of Science Worsaw, Poland.
    Ludwigs, Ulf
    Södersjukhuset Stockholm.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Matuszewski, A
    Polish Academy of Science Warsaw, Poland.
    Baehrendz, S
    Karolinska Institutet Stockholm.
    Matell, George
    Karolinska Institutet Stockholm.
    Statistical models for prediction of arterial oxygen and carbon dioxide tensions during mechanical ventilation1991In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 34, p. 191-199Article in journal (Refereed)
  • 37.
    Saeedi, Baharak
    et al.
    Linköping University, Department of Molecular and Clinical Medicine, Clinical Microbiology. Linköping University, Faculty of Health Sciences.
    Tärnberg, Maria
    Linköping University, Department of Clinical and Experimental Medicine, Clinical Microbiology. Linköping University, Faculty of Health Sciences.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Hällgren, Anita
    Linköping University, Department of Molecular and Clinical Medicine, Clinical Microbiology. Linköping University, Faculty of Health Sciences.
    Jonasson, Jon
    Linköping University, Department of Molecular and Clinical Medicine, Clinical Microbiology. Linköping University, Faculty of Health Sciences.
    Nilsson, Lennart
    Linköping University, Department of Molecular and Clinical Medicine, Clinical Microbiology. Linköping University, Faculty of Health Sciences.
    Isaksson, Barbro
    Linköping University, Department of Molecular and Clinical Medicine, Clinical Microbiology. Linköping University, Faculty of Health Sciences.
    Kühn, I.
    Department of Microbiology and Tumour Biology Centre, Karolinska Institute, Stockholm, Sweden.
    Hanberger, Håkan
    Linköping University, Department of Molecular and Clinical Medicine, Infectious Diseases. Linköping University, Faculty of Health Sciences.
    Phene Plate (PhP) biochemical fingerprinting: a screening method for epidemiological typing of enterococcal isolates?2005In: Acta Pathologica, Microbiologica et Immunologica Scandinavica (APMIS), ISSN 0903-4641, E-ISSN 1600-0463, Vol. 113, no 9, p. 603-612Article in journal (Refereed)
    Abstract [en]

    Pulsed-field gel electrophoresis (PFGE) is currently considered the gold standard for genotyping of enterococci. However, PFGE is both expensive and time-consuming. The purpose of this study was to investigate whether the PhP system can be used as a reliable clinical screening method for detection of genetically related isolates of enterococci. If so, it should be possible to minimize the number of isolates subjected to PFGE typing, which would save time and money. Ninety-nine clinical enterococcal isolates were analysed by PhP (similarity levels 0.90–0.975) and PFGE (similarity levels ≤3 and ≤6 bands) and all possible pairs of isolates were cross-classified as matched or mismatched. We found that the probability that a pair of isolates (A and B) belonging to the same type according to PhP also belong to the same cluster according to PFGE, i.e. p(APFGE=BPFGE • APhP=BPhP), and the probability that a pair of isolates of different types according to PhP also belong to different clusters according to PFGE, i.e. p(APFGE≠BPFGE • APhP≠BPhP), was relatively high for E. faecalis (0.86 and 0.96, respectively), but was lower for E. faecium (0.51 and 0.77, respectively). The concordance which shows the probability that PhP and PFGE agree on match or mismatch was 86%–93% for E. faecalis and 54%–66% for E. faecium, which indicates that the PhP method may be useful for epidemiological typing of E. faecalis in the current settings but not for E. faecium.

  • 38.
    Samuelsson, Per Johan
    et al.
    IMT LiU.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Lassvik, Clas
    Klin Fys, US .
    Linnarsson, Dag
    KI Stockholm.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ramp-function work test suitable for automatic computation1986In: Clinical Physiology, ISSN 0144-5979, E-ISSN 1365-2281, Vol. 6, p. 53-62Article in journal (Refereed)
  • 39.
    Shahsavar, Nosrat
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ludwigs, Ulf
    Södersjukhuset Stockholm.
    Carstensen, A
    Södersjukhuset Stockholm.
    Larsson, H
    Dept of Med Engineering Huddinge sjukhus.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Matell, George
    Södersjukhuset Stockholm.
    VentEx: an on-line knowledge-based system to support ventilator management1994In: Technology and Health Care, ISSN 0928-7329, Vol. 1, p. 233-243Article in journal (Refereed)
  • 40.
    Shahsavar, Nosrat
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Frostell, Claes
    Danderyds Hospital .
    Matell, George
    Södersjukhuset Stockholm.
    Ludwigs, Ulf
    Södersjukhuset Stockholm.
    KAVE: a tool for knowledge acquisition to support artificial ventilation1991In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 34, p. 115-123Article in journal (Refereed)
  • 41.
    Shahsavar, Nosrat
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ludwigs, Ulf
    Södersjukhuset Stockholm.
    Blomqvist, Hans
    Danderyds sjukhus .
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Matell, George
    Södersjukhuset Stockholm.
    Evaluation of a knowledge-based decision-support system for ventilator therapy management1995In: Artificial Intelligence in Medicine, ISSN 0933-3657, E-ISSN 1873-2860, Vol. 7, p. 37-52Article in journal (Refereed)
  • 42.
    Thurin, Anders
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Carlsson, Mats
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Arden Syntax and GALEN terminology support: A poweful combination to represent medical knowledge1995In: MEDINFO95,1995, Edmonton: HC & CC , 1995, p. 110-Conference paper (Refereed)
  • 43.
    Walther, Sten
    et al.
    Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Erlandsson, M.
    Linköping University, Department of Clinical and Experimental Medicine, Infectious Diseases . Linköping University, Faculty of Health Sciences.
    Olsson-Liljequist, B.
    Smittskyddsinstitutet, Solna, Sweden.
    Hanberger, Håkan
    Linköping University, Department of Clinical and Experimental Medicine, Infectious Diseases . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medicine, Department of Infectious Diseases in Östergötland.
    The Icustrama Study Group (2002),
    Burman, L.G.
    Smittskyddsinstitutet, Solna, Sweden.
    Cars, O.
    Smittskyddsinstitutet, Solna, Sweden.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Hoffman, Mikael
    Linköping University, Department of Medicine and Health Sciences, Clinical Pharmacology . Linköping University, Faculty of Health Sciences.
    Isaksson, Barbro
    Linköping University, Department of Clinical and Experimental Medicine, Clinical Microbiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Laboratory Medicine, Department of Clinical Microbiology.
    Kahlmeter, G.
    Department of Clinical Microbiology, Växjö lasarett.
    Lindgren, S.
    Nilsson, Lennart
    Linköping University, Department of Clinical and Experimental Medicine, Clinical Microbiology . Linköping University, Faculty of Health Sciences.
    Antibiotic prescription practices, consumption and bacterial resistance in a cross section of Swedish intensive care units2002In: Acta Anaesthesiologica Scandinavica, ISSN 0001-5172, Vol. 46, no 9, p. 1075-1081Article in journal (Refereed)
    Abstract [en]

    Background: The purpose of this work was to study usage of antibiotics, its possible determinants, and patterns of bacterial resistance in Swedish intensive care units (ICUs).

    Methods: Prospectively collected data on species and antibiotic resistance of clinical isolates and antibiotic consumption specific to each ICU in 1999 were analyzed together with answers to a questionnaire. Antibiotic usage was measured as defined daily doses per 1000 occupied bed days (DDD1000).

    Results: Data were obtained for 38 ICUs providing services to a population of approximately 6 million. The median antibiotic consumption was 1257 DDD1000 (range 584–2415) and correlated with the length of stay but not with the illness severity score or the ICU category. Antibiotic consumption was higher in the ICUs lacking bedside devices for hand disinfection (2193 vs. 1214 DDD1000, p=0.05). In the ICUs with a specialist in infectious diseases responsible for antibiotic treatment the consumption pattern was different only for use of glycopeptides (58% lower usage than in other ICUs: 26 vs. 11 DDD1000,P=0.02). Only 21% of the ICUs had a written guideline on the use of antibiotics, 57% received information on antibiotic usage at least every 3 months and 22% received aggregated resistance data annually. Clinically significant antimicrobial resistance was found among Enterbacter spp. to cephalosporins and among Enterococcus spp. to ampicillin.

    Conclusions: Availability of hand disinfection equipment at each bed and a specialist in infectious diseases responsible for antibiotic treatment were factors that correlated with lower antibiotic consumption in Swedish ICUs, whereas patient-related factors were not associated with antibiotic usage.

  • 44.
    Walther, Sten
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Jonasson, U
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Comparison of the Glasgow Coma Scale and the Reaction Level Scale for assessment of cerebral responsiveness in the critically ill2003In: Intensive Care Medicine, ISSN 0342-4642, E-ISSN 1432-1238, Vol. 29, no 6, p. 933-938Article in journal (Refereed)
    Abstract [en]

    Objective: The Glasgow Coma Scale (GCS) is a well-known source of error in outcome prediction models. We compared assessment of cerebral responsiveness with the GCS and the Reaction Level Scale (RLS) in two otherwise similar outcome prediction models. Design and setting: Prospective, observational study in a general intensive care unit. Patients and participants: All admissions of patients with or at risk of developing impaired brain function between 1997 and 1998 (n=534). Measurements and results: Admissions were scored by RLS and APACHE II (includes scoring with the GCS). The RLS scores were transformed to APACHE II central nervous system scores according to a predetermined protocol. APACHE II estimated probability of death was calculated conventionally with the GCS and the RLS. Vital status 90 days after admission was secured from a national database. Bias and precision was 0.5% and 16.6%, respectively. The area under receiver operating characteristic curves was slightly but significantly greater with the RLS-based APACHE 11 model than with the GCS-based model (0.92 vs. 0.90). Discrimination was improved primarily in admissions with low and intermediate probability of death. Conclusions: Scoring of cerebral responsiveness with the RLS instead of the GCS was associated with minimal bias of the APACHE 11 probability of death estimate. Assessment of consciousness in critically ill with the RLS deserves further evaluation.

  • 45.
    Walther, Sten
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Anaesthesiology. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Jonasson, Ulla
    Norrköping.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering.
    A comparison of The Glasgow coma scale and the reaction level scale in the critically ill.2003In: Intensive Care Medicine, ISSN 0342-4642, E-ISSN 1432-1238, Vol. 29, p. 933-938Article in journal (Refereed)
  • 46.
    Wigertz, Ove
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Chowdhury, Shamsul
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Xiao-Ming, Gao
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Johansson, Bo
    IMT LiU.
    Validation of medical logics in the Arden syntax knowledge representation1992In: MEDICON92 Mediterrean conference on medical and biological engineering,1992, Pisa: AREADI RICERCA , 1992, p. 1051-Conference paper (Refereed)
  • 47.
    Wigertz, Ove
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Teaching medical informatics to medical students1990In: Int Conference on Medical Informatics and Medical Education IMIA,1990, Elsevier Science Publ , 1990, p. 41-Conference paper (Refereed)
  • 48.
    Wigertz, Ove
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Teaching medical informatics to medical students1991In: IMIA Int Conference on Medical Informatics and Medical Education,1990, Amsterdam: Elsevier Science Publishers , 1991, p. 41-Conference paper (Refereed)
  • 49.
    Wigertz, Ove
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Hripcsak, George
    Columbia Presbyterian Medical Center New York.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Bågenholm, Per
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Data-driven medical knowled-based systems based on Arden Syntax1994In: Knowledge and Decisions in Health Telematics / [ed] P. Barahona, J.P. Christensen, Amsterdam: IOS Press , 1994, p. 126-131Chapter in book (Other academic)
  • 50.
    Wigertz, Ove
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Xiao-Ming, Gao
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Jönsson, Kjell-Åke
    Dept of Medicine Linköping University Hospital.
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ohlsson, Per
    IMT .
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Knowledge representation for an anticoagulant therapy advisorArkad1993In: Int Congress of the European Federation for Medical Informatics MIE93,1993, London, England: Freund Publishing House Ltd , 1993, p. 99-Conference paper (Refereed)
12 1 - 50 of 52
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